Estimating Mangrove Above-Ground Biomass Using Extreme Gradient Boosting Decision Trees Algorithm wi...
Estimating Mangrove Above-Ground Biomass Using Extreme Gradient Boosting Decision Trees Algorithm with Fused Sentinel-2 and ALOS-2 PALSAR-2 Data in Can Gio Biosphere Reserve, Vietnam
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MDPI AG
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English
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MDPI AG
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This study investigates the effectiveness of gradient boosting decision trees techniques in estimating mangrove above-ground biomass (AGB) at the Can Gio biosphere reserve (Vietnam). For this purpose, we employed a novel gradient-boosting regression technique called the extreme gradient boosting regression (XGBR) algorithm implemented and verified...
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Full title
Estimating Mangrove Above-Ground Biomass Using Extreme Gradient Boosting Decision Trees Algorithm with Fused Sentinel-2 and ALOS-2 PALSAR-2 Data in Can Gio Biosphere Reserve, Vietnam
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TN_cdi_doaj_primary_oai_doaj_org_article_2c53ff157a3d4506a57dd10e25ac5a9c
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_2c53ff157a3d4506a57dd10e25ac5a9c
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ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs12050777
